Bibliographic record
Abstract
The worldwide small arms epidemic must be controlled In the wake of September 11, it is more obvious than ever that small arms can bring about large carnage, and that they will continue to figure prominently in regional conflicts. It is no exaggeration to say that it is now urgent to understand the public health crises linked to small arms, and to devise means to minimize these. This commentary offers some information and thoughts to inform the discourse in the health arena drawn from an international conference. The first ever large international meeting on guns was held in New York, 9–20 July 2001. The meeting was the “United Nations Conference on the Illicit Trade in Small Arms And Light Weapons In All Its Aspects”. I attended the meeting as a representative of the Handgun Epidemic Lowering Plan (HELP) Network (www.helpnetwork.org). HELP was one of a small contingent promoting public health as part of “all the aspects”. Most of the hundreds of involved non-governmental organizations (NGOs) approach small arms as an issue that is primarily related to war and crime. The goal of the health groups was to strengthen awareness of health perspectives on reducing the international toll of small arms. While a Canadian view on this has recently been published1 the current commentary summarizes what another North American health professional learned from the meeting. In 2000, the United Nations adopted a new Convention Against Transnational Organized Crime. In May 2001, the United Nations General Assembly added a “Firearm Protocol” to the Convention, intended to “promote, facilitate and strengthen cooperation among State parties in order to prevent, combat, and eradicate the illicit manufacturing and trafficking in firearms, their parts, components and ammunition”.2 The July 2001 meeting was organized to address the issue of small arms “more comprehensively”. The definition …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".